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000001203221
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20251013091534
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ta
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251010s2025 uk b 001c0 eng
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020
▼a 9781032788128
▼q (hbk) -
020
▼a 9781032788135
▼q (pbk) -
020
▼z 9781003489368
▼q (ebk) -
035
▼a (KERIS)REF000020706770
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040
▼a DLC
▼b eng
▼c DLC
▼d DLC
▼e rda
▼d 211070 -
042
▼a pcc
-
050
▼a TK5103.7
-
090
▼a TK5103.7
▼b K61 -
245
▼a Federated learning for smart communications using IoT application /
▼d Kaushal Kishor,
▼e Parma Nand,
▼e Vishal Jain,
▼e Neetesh Saxena,
▼e Gaurav Agarwal,
▼e Rani Astya -
250
▼a 1st ed.
-
260
▼a Boca Raton :
▼b C&H/CRC Press,
▼c 2025 -
300
▼a 260 p. ;
▼c 24 cm -
490
▼a Chapman & Hall/CRC cyber-physical systems
-
504
▼a Includes bibliographical references and index.
-
520
▼a "The book aims to demonstrate the effectiveness of federated learning in high-performance information systems and informatics-based solutions for addressing current information support requirements. To address heterogeneity challenges in IoT contexts, it analyses the development of personalized federated learning algorithms capable of mitigating the detrimental consequences of heterogeneity in several dimensions. It includes case studies of IoT-based human activity recognition to demonstrate the efficacy of personalized federated learning for intelligent IoT applications. Demonstrates how federated learning offers a novel approach to building personalized models from data without invading users' privacy Describes how federated learning may assist in understanding and learning from user behavior in Internet of Things (IoT) applications while safeguarding user privacy Presents a detailed analysis of current research on federated learning, providing the reader with a broad understanding of the area Analyses the need for a personalized federated learning framework in cloud-edge and wireless-edge architecture for intelligent IoT applications Comprises real-life case illustrations and examples to help consolidate understanding of topics presented in each chapter This book is recommended for anybody interested in Federated Learning-based Intelligent Algorithms for Smart Communications"--
▼c Provided by publisher -
650
▼a Digital communications
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650
▼a Ensemble learning (Machine learning)
-
650
▼a Machine learning
▼x Security measures -
650
▼a Internet of things
▼x Security measures -
650
▼a Medical records
▼x Security measures -
700
▼a Kishor, Kaushal,
▼e editor -
830
▼a Chapman & Hall/CRC cyber-physical systems
-
950
▼b ￡145
-
991
▼a 단행본
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Detailed Information
Federated learning for smart communications using IoT application 1st ed
QR Code| Data Type : | 단행본 |
|---|---|
| ISBN : | 9781032788128 |
| ISBN : | 9781032788135 |
| ISBN : | |
| Class No. : | TK5103.7 |
| Title/Author : | Federated learning for smart communications using IoT application / Kaushal Kishor, Parma Nand, Vishal Jain, Neetesh Saxena, Gaurav Agarwal, Rani Astya |
| Edition : | 1st ed. |
| Imprint : | Boca Raton : C&H/CRC Press, 2025 |
| Format : | 260 p. ; 24 cm |
| Total Title Note : | Chapman & Hall/CRC cyber-physical systems |
| Note : | Includes bibliographical references and index. |
| 요약 : | "The book aims to demonstrate the effectiveness of federated learning in high-performance information systems and informatics-based solutions for addressing current information support requirements. To address heterogeneity challenges in IoT contexts, it analyses the development of personalized federated learning algorithms capable of mitigating the detrimental consequences of heterogeneity in several dimensions. It includes case studies of IoT-based human activity recognition to demonstrate the efficacy of personalized federated learning for intelligent IoT applications. Demonstrates how federated learning offers a novel approach to building personalized models from data without invading users' privacy Describes how federated learning may assist in understanding and learning from user behavior in Internet of Things (IoT) applications while safeguarding user privacy Presents a detailed analysis of current research on federated learning, providing the reader with a broad understanding of the area Analyses the need for a personalized federated learning framework in cloud-edge and wireless-edge architecture for intelligent IoT applications Comprises real-life case illustrations and examples to help consolidate understanding of topics presented in each chapter This book is recommended for anybody interested in Federated Learning-based Intelligent Algorithms for Smart Communications"-- Provided by publisher |
| General Subject Name : | Digital communications -- |
| General Subject Name : | Ensemble learning (Machine learning) -- |
| General Subject Name : | Machine learning -- Security measures -- |
| General Subject Name : | Internet of things -- Security measures -- |
| General Subject Name : | Medical records -- Security measures -- |
| Personal Author : | Kishor, Kaushal, editor |
| Language | English |
예약
- 1. 예약현황은 홈페이지 로그인 후 예약 페이지에 확인 가능합니다.
- 2. 도착 통보된 예약자료 대출을 원하지 않는 경우에는 예약 현황에서 취소할 수 있습니다.
- 3. 기타 문의사항은 도서관에 문의 바랍니다.
무인예약대출
- 1. 무인예약대출 현황은 홈페이지 로그인 후 무인예약대출 페이지에 확인 가능합니다.
- 2. 무인예약대출자료 대출을 원하지 않는 경우에는 무인예약대출 페이지에서 신청 또는 접수상태인 경우만 취소할 수 있습니다.
- 3. 희망대출일은 신청일로부터 최대 1주일 까지 가능합니다.
- 4. 희망대출일을 선택하지 않은 경우 대출대기 통보 후 1주일까지 기기에서 대출가능합니다.
- 5. 기타 문의사항은 도서관에 문의 바랍니다.
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